MIT Engineers
2026 Team Stats (1 games)
50.0
PPG
79.0
Opp
-29.0
Margin
27.8%
FG%
10.7%
3P%
85.0%
FT%
34.0
RPG
6.0
APG
12.0
TO
74.8
Pace
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 998 (#230) | HCA +109 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -4.2 (#410) | HCA +2.5 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.486 (#304) | AdjO 72.7 | AdjD 73.3 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.362 (#426) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. More → | 0.382 (#421) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 929 (#379) | RD 350 | GP 1 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-07 | @ | Harvard Crimson | L | 50 - 79 |
2026 Roster
Minutes by Position
The surface stays filled across the five on-court roles. Use the labels or legend to isolate how each player absorbs guard-to-big minutes.
| Player | Pos | GP | MIN | PTS | REB | AST | STL | BLK | TO | FGA | Numbers | PM | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
I. Dobie
|
- | 1 | 29.0 | 17.0 | 6.0 | 1.0 | 1.0 | 0.0 | 3.0 | 12.0 | 10.0 | - | - | - | 41.7 | 14.3 | 75.0 | - | 54.8 | 45.8 |
J. Weiland
|
- | 1 | 31.0 | 11.0 | 9.0 | 2.0 | 1.0 | 0.0 | 1.0 | 4.0 | 18.0 | - | - | - | 75.0 | 50.0 | 100.0 | - | 95.5 | 87.5 |
M. Ewing
|
- | 1 | 22.0 | 9.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 6.0 | 3.0 | - | - | - | 33.3 | 50.0 | 100.0 | - | 58.0 | 41.7 |
R. Delgado-Gonzalez
|
- | 1 | 35.0 | 8.0 | 5.0 | 0.0 | 0.0 | 0.0 | 1.0 | 9.0 | 3.0 | - | - | - | 33.3 | 0.0 | 100.0 | - | 40.5 | 33.3 |
M. Zhang
|
- | 1 | 32.0 | 3.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 13.0 | -9.0 | - | - | - | 7.7 | 0.0 | 50.0 | - | 10.8 | 7.7 |
W. Mowery
|
- | 1 | 23.0 | 2.0 | 6.0 | 2.0 | 1.0 | 3.0 | 1.0 | 8.0 | 5.0 | - | - | - | 12.5 | 0.0 | 0 | - | 12.5 | 12.5 |
Woods Windham
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Will Bland
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
S. Chen
|
- | 1 | 10.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Daniel Allen
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | 167 | 8.8 | 16.2 | - | - | - | 1.62 | - | - |
Parker Spann
|
F | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
H. Marshall
|
- | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
M. Gogolin
|
- | 1 | 17.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 3.0 | 2.0 | -2.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
Paulius Karvelis
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Yusuf Young
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Dusan Dobric
|
C | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Numbers/Game vs RAPM
Not enough players with both Numbers/Game and RAPM to plot.
Advanced: Numbers = PTS+REB+AST+STL+BLK-TO-FGA, PM = total +/-, PM/G = per game, PM/40 = per 40 minutes, RAPM = Regularized Adj Plus-Minus, TS% = True Shooting, eFG% = Effective FG